Space and Time (SxT), a verifiable compute layer known for its Verifiable Compute Layer that integrates artificial intelligence (AI) and blockchain, has launched Proof of SQL, a high-performance, zero-knowledge (ZK) prover for data processing, according to the latest updates shared with Finbold on June 12.
This innovative ZK proof ensures cryptographic accuracy for SQL database queries against unaltered data.
Proof of SQL is publicly accessible via GitHub, and community members can execute trustless queries on SxT via the Space and Time Studio.
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Seamless computing both on-chain and off-chain
With Proof of SQL, developers can seamlessly compute both on-chain and off-chain datasets in a trustless way, validating results back to their smart contracts in real-time during transactions.
This advancement is set to enhance the capabilities of data-driven smart contracts in decentralized finance (DeFi) protocols.
Jay White, PhD, Co-Founder and Head of Research at SxT, expressed enthusiasm for the next generation of DeFi:
“Space and Time is thrilled to lead Web3 into a new era of data-driven smart contracts and the next generation of DeFi. Our team pioneered sub-second ZK proofs so that smart contracts and AI agents can ask questions about a chain’s activity, as well as offchain data, and receive back trustless SQL query results onchain during a transaction without having to wait for 30 minute proof times.”
Sub-second performance of Proof of SQL
Proof of SQL is the first ZK prover capable of sub-second performance.
Recent benchmarks conducted by the SxT cryptography team show the protocol can execute analytic queries over 100,000-row tables in under a second on a single GPU.
It can also aggregate millions of rows of indexed data within Ethereum (ETH) block time using a single NVIDIA T4.
This is a more efficient solution for processing large data volumes compared to generalized zkVMs and co-processors.
Proof of SQL can be integrated with these zkVMs to provide verifiable source data for executing arbitrary code.
The prover can be incorporated into any SQL database, such as Google BigQuery, whether centralized or decentralized.
